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@article{169353,
        author = {Sanjay Gandhi Gundabatini and Shaik Nazeema},
        title = {Real-Time Text Detection and Translation Using OpenCV and Tesseract OCR: An Integrated Framework for Images and Videos},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {2133-2139},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169353},
        abstract = {In an increasingly interconnected world, real-time text detection and translation have become essential for seamless communication across linguistic barriers. This research presents a real-time framework for text detection, recognition, and translation using OpenCV and Tesseract OCR, designed for both image and video inputs. The system extracts frames from video streams, preprocesses them to enhance text visibility, and uses Tesseract OCR for text extraction. The recognized text is then translated and displayed on screen in real-time. The framework is highly efficient and versatile, suitable for applications such as real-time language translation, aiding non-native speakers, and enhancing accessibility for the visually impaired. Achieves a much higher accuracy rate of 95% in detecting and recognizing text, which indicates significant improvement. Experimental results confirm the system's effectiveness, with high accuracy and low latency, making it ideal for real-time deployment.},
        keywords = {Real-time text detection, OCR, Tesseract OCR, OpenCV, video processing, webcam input, text translation, frame extraction, image preprocessing, language accessibility, Machine Learning, real-time translation.},
        month = {November},
        }